




"""simple docstring"""






import argparse

import torch

from transformers import YosoConfig, YosoForMaskedLM







def 	_snake_case     (							lowercase__						):
				if "model" in orig_key:
								_lowerCamelCase	:     Dict       =       orig_key.replace('model.'				,       ''						)
				if "norm1" in orig_key:
								_lowerCamelCase	:     List[Any]       =       orig_key.replace('norm1'				,       'attention.output.LayerNorm'						)
				if "norm2" in orig_key:
								_lowerCamelCase	:     List[str]       =       orig_key.replace('norm2'				,       'output.LayerNorm'						)
				if "norm" in orig_key:
								_lowerCamelCase	:     Tuple       =       orig_key.replace('norm'				,       'LayerNorm'						)
				if "transformer" in orig_key:
								_lowerCamelCase	:     Tuple       =       orig_key.split('.'						)[0].split('_'						)[-1]
								_lowerCamelCase	:     Dict       =       orig_key.replace(f'''transformer_{layer_num}'''				,       f'''encoder.layer.{layer_num}'''						)
				if "mha.attn" in orig_key:
								_lowerCamelCase	:     List[Any]       =       orig_key.replace('mha.attn'				,       'attention.self'						)
				if "mha" in orig_key:
								_lowerCamelCase	:     Optional[int]       =       orig_key.replace('mha'				,       'attention'						)
				if "W_q" in orig_key:
								_lowerCamelCase	:     Any       =       orig_key.replace('W_q'				,       'self.query'						)
				if "W_k" in orig_key:
								_lowerCamelCase	:     List[str]       =       orig_key.replace('W_k'				,       'self.key'						)
				if "W_v" in orig_key:
								_lowerCamelCase	:     Any       =       orig_key.replace('W_v'				,       'self.value'						)
				if "ff1" in orig_key:
								_lowerCamelCase	:     int       =       orig_key.replace('ff1'				,       'intermediate.dense'						)
				if "ff2" in orig_key:
								_lowerCamelCase	:     int       =       orig_key.replace('ff2'				,       'output.dense'						)
				if "ff" in orig_key:
								_lowerCamelCase	:     List[str]       =       orig_key.replace('ff'				,       'output.dense'						)
				if "mlm_class" in orig_key:
								_lowerCamelCase	:     Union[str, Any]       =       orig_key.replace('mlm.mlm_class'				,       'cls.predictions.decoder'						)
				if "mlm" in orig_key:
								_lowerCamelCase	:     Dict       =       orig_key.replace('mlm'				,       'cls.predictions.transform'						)
				if "cls" not in orig_key:
								_lowerCamelCase	:     Tuple       =       'yoso.' + orig_key

				return orig_key







def 	_snake_case     (							lowercase__				,       lowercase__						):
				for key in orig_state_dict.copy().keys():
								_lowerCamelCase	:     Optional[int]       =       orig_state_dict.pop(UpperCamelCase__						)

								if ("pooler" in key) or ("sen_class" in key):
												continue
								else:
												_lowerCamelCase	:     Dict       =       val

				_lowerCamelCase	:     Dict       =       orig_state_dict['cls.predictions.decoder.bias']
				_lowerCamelCase	:     Optional[Any]       =       torch.arange(UpperCamelCase__						).expand((1, -1)						) + 2

				return orig_state_dict







def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__						):
				_lowerCamelCase	:     int       =       torch.load(UpperCamelCase__				,       map_location='cpu'						)['model_state_dict']
				_lowerCamelCase	:     List[Any]       =       YosoConfig.from_json_file(UpperCamelCase__						)
				_lowerCamelCase	:     int       =       YosoForMaskedLM(UpperCamelCase__						)

				_lowerCamelCase	:     Any       =       convert_checkpoint_helper(config.max_position_embeddings				,       UpperCamelCase__						)

				print(model.load_state_dict(UpperCamelCase__						)						)
				model.eval()
				model.save_pretrained(UpperCamelCase__						)

				print(f'''Checkpoint successfuly converted. Model saved at {pytorch_dump_path}'''						)


if __name__ == "__main__":
			lowercase__			=		argparse.ArgumentParser()
			# Required parameters
			parser.add_argument(
			    """--pytorch_model_path""", default=None, type=str, required=True, help="""Path to YOSO pytorch checkpoint."""
			)
			parser.add_argument(
			    """--config_file""",
			    default=None,
			    type=str,
			    required=True,
			    help="""The json file for YOSO model config.""",
			)
			parser.add_argument(
			    """--pytorch_dump_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
			)
			lowercase__			=		parser.parse_args()
			convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)
'''simple docstring'''




def __lowerCAmelCase					(				)      ->       Optional[Any]:
    __lowerCamelCase            =    0
    for i in range(1							,    10_01							):
        total += i**i
    return str(UpperCamelCase__							)[-10:]


if __name__ == "__main__":
  print(solution())
